Application of genetic algorithms to semiconductor supply chain planning

Rama Chidambaram, Hans Armbruster

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

One of the fundamental challenges of modeling a semiconductor supply chain has been to develop a computationally tractable model that can also reflect the non-linear Throughput Time (TPT) of manufacturing. The non-linear increase in throughput time can be modeled as a function of the input to the manufacturing facility. An efficient semiconductor production-planning algorithm has to capture the non-linear throughput time of production to avoid significant differences between the planned and realized output. In this paper we propose a Linear Programming (LP) and Genetic Algorithm (GA) framework to capture the non-linear nature of the TPT time in supply chain planning.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 International Conference on Algorithmic Mathematics and Computer Science, AMCS'05
Pages77-83
Number of pages7
StatePublished - Dec 1 2005
Event2005 International Conference on Algorithmic Mathematics and Computer Science, AMCS'05 - Las Vegas, NV, United States
Duration: Jun 20 2005Jun 23 2005

Publication series

NameProceedings of the 2005 International Conference on Algorithmic Mathematics and Computer Science, AMCS'05

Other

Other2005 International Conference on Algorithmic Mathematics and Computer Science, AMCS'05
CountryUnited States
CityLas Vegas, NV
Period6/20/056/23/05

Keywords

  • Genetic algorithm
  • Linear programming
  • Supply chain
  • Throughput time

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Theoretical Computer Science

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